Ad hoc supply chain community node

ABSTRACT

An ad hoc supply chain collaborative computing environment management method includes selecting a collaboration model from amongst several models and establishing the environment in accordance with the selected model including defining a knowledge graph, a set of expected events to be received in an event log, and one or more predictive functions operating upon the different events in the event log to produce predictive values. The method also includes, registering actors in a supply chain as authenticated publishers or subscribers to the event log of different events published by different authenticated computing systems of the actors, authenticating different ones of the registered different actors prior the different actors publishing events to the event log, triggering predictive functions for newly published ones of the events in order to produce predictive values and providing read-only access to different states of the entities of the knowledge graph to authenticated subscribers.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention relates to the field of logistics data sharing andvisibility and more particularly to collaborative logistics data sharingand visibility in supply chain management.

Description of the Related Art

A supply chain is a network between a company and its suppliers toproduce and distribute a specific product, and the supply chainrepresents the steps it takes to get the product or service to thecustomer. Supply chain management is a crucial process because anoptimized supply chain results in lower costs and a faster productioncycle. Business logistics management refers to the production anddistribution process within the company, while supply chain managementincludes suppliers, manufacturers, logistics and transportationcompanies and retailers that distribute the product to the end customer.Supply chains include every business that comes in contact with aparticular product, including companies that assemble and deliver partsto the manufacturer.

Because the traditional supply chain involves many different actorsutilizing many different disparate information systems, informationsharing amongst the different actors can be challenging. Transparencyinto the state of affairs of a given transaction depends largely uponthe willingness and diligence of each actor in the supply chain of thetransaction to provide accurate and timely information to one another.In a single transaction, so much seems not so daunting, but in a supplychain ecosystem of hundreds if not thousands of transactions are ongoingat any given time and much of the resources available within theecosystem—particularly in respect to transportation and logistics—remaindependent upon the state of multiple different transactions.

In this regard, in any supply chain ecosystem, it is the unstated goalto optimize the utilization of all resources in the supply chain so asto most effectively and optimally bring products from source to sink.But, given the multiplicity of different actors in the supply chain andthe disparity of information provided by each actor, optimization of thesupply chain remains nearly impossible. To compound matters, supplychain participants vary in their willingness to share supply chaininformation deemed sensitive, confidential and therefore, notappropriate for public consumption.

BRIEF SUMMARY OF THE INVENTION

Embodiments of the present invention address deficiencies of the art inrespect to supply chain information sharing and provide a novel andnon-obvious method, system and computer program product for an ad hocsupply chain collaborative computing environment adapted for supplychain information sharing amongst actors in a supply chain so as topromote supply chain information sharing amongst participants in asupply chain in a private and confidential manner and therefore topromote supply chain resource utilization optimization. In an embodimentof the invention, an ad hoc supply chain collaborative computingenvironment includes a host computing system of one or more computers,each with memory and at least one processor and a data store coupled tothe host computing system and adapted to persist data therein. Thecollaborative computing environment also includes a collaboration modelstored in the memory and selected from amongst a multiplicity ofcollaboration models. Each of the collaboration models corresponds to adifferent set of data sharing requirements in a supply chain and acts asa template for an instance of an ad hoc supply chain collaborativecomputing environment.

In this regard, each of the collaboration models defines a specific typeof knowledge graph that includes different entities representative ofcorresponding actors and resources of the supply chain necessary tofulfill data processing requirements of the different set, joined byedges representative of relationships between respectively joined onesof the entities. Each of the collaboration models also defines a set ofevents expected to be received in connection with the data sharingrequirements. Finally, each of the collaboration models defines one ormore predictive functions operating upon the set of events to producepredictive values.

The collaborative computing environment thus also includes a knowledgegraph initialized in accordance with the selected collaboration modeland persisted in the data store and that includes different entitiesrepresentative of corresponding resources of a supply chain, joined byedges representative of relationships between respectively joined onesof the entities. Of note, an event log is persisted in the data storeand includes different events published to the event log in accordancewith the selected collaboration model by different authenticatedcomputing systems of the actors.

Finally, the supply chain collaborative computing environment includes asupply chain collaborative computing environment module. The moduleincludes program instructions executing in the memory of the hostcomputing system in order to perform first registering different actorsin the supply chain as authenticated publishers or subscribers to theevent log and mapping events occurring in information systems ofrespective ones of the actors to the events of the selectedcollaboration model. The program instructions also authenticatedifferent ones of the registered actors prior the different ones of theactors publishing events to the event log. The program instructions yetfurther trigger selected ones of the predictive functions for newlypublished ones of the events mapped to the selected ones of thepredictive functions in order to produce the predictive values. Finally,the program instructions compute different states of the entities of theknowledge graph responsive to the predictive values produced by thepredictive functions and provide read-only access to the differentstates of the entities of the knowledge graph to authenticatedsubscriber ones of the actors through an interface to the supply chaincollaborative computing environment module.

In one aspect of the embodiment, the program instructions are furtherenabled to provide access to the different states of the entities of theknowledge graph by other supply chain collaborative computingenvironments in an aggregation of interoperable supply chaincollaborative computing environments. In another aspect of theembodiment, the supply chain collaborative computing environment furtherincludes a search engine interface configured to conduct search queriespresented through the search engine interface against both the knowledgegraph and also the event log. In yet another aspect of the embodiment,the supply chain collaborative computing environment includes a set ofkey performance indicators (KPIs) defined in the data store, with atleast one of the predictive functions determining a change in one of theKPIs based at least one of the newly published ones of the events. Ineven yet another aspect of the embodiment, the supply chaincollaborative computing environment includes one or more access rulesdisposed in the data store each rule defining a limitation on accessingstate information for entities of the knowledge graph based upon anidentity of a corresponding one of the actors seeking access to thestate information.

Finally, in even yet another aspect of the embodiment, the collaborationmodels include at least one model directed to data sharing requirementsfor retail stock optimization. As well, the collaboration models includeat least one model directed to data sharing requirements fortransportation and logistics resource and capacity optimization. Evenfurther, the collaboration models include at least one model directed todata sharing requirements for logistics pooling and integration forurban distribution. Even yet further, the collaboration models includeat least one model directed to data sharing requirements for electroniccompliance with governmental regulations. Finally, the collaborationmodels include at least one model directed to data sharing requirementsfor supply chain financial management.

In another embodiment, an ad hoc supply chain collaborative computingenvironment management method is provided. The method includespresenting in a user interface of a host computing system, a list ofcollaboration models, each corresponding to a different set of datasharing requirements in a supply chain and acting as a template for aninstance of an ad hoc supply chain collaborative computing environment,each corresponding to a different set of data sharing requirements in asupply chain and acts as a template for an instance of an ad hoc supplychain collaborative computing environment. The method also includesselecting in the user interface, one of the collaborative models and inresponse to the selection, initializing in memory of the host computingsystem in accordance with the selected collaboration model, a knowledgegraph comprising different entities representative of correspondingresources of the supply chain, joined by edges representative ofrelationships between respectively joined ones of the entities.

The method yet further includes registering by a processor of a hostcomputing system different actors in a supply chain as authenticatedpublishers or subscribers to an event log persisted in a data storecoupled to the host computing system and comprising different eventspublished to the event log defined in accordance with the selectedcollaboration model and by different authenticated computing systems ofthe actors and mapping events occurring in information systems ofrespective ones of the actors to the events of the selectedcollaboration model. The method yet further includes authenticating bythe processor different ones of the registered different actors priorthe different actors publishing events to the event log. The method evenyet further includes triggering by the processor selected ones of thepredictive functions for newly published ones of the events mapped tothe selected ones of the predictive functions in order to produce thepredictive values. Finally, the method includes generating by theprocessor different states of the entities of the knowledge graphresponsive to the predictive values produced by the predictive functionsand providing by the processor read-only access to the different statesof the entities of the knowledge graph to authenticated subscriber onesof the actors through an interface to the supply chain collaborativecomputing environment module.

Additional aspects of the invention will be set forth in part in thedescription which follows, and in part will be obvious from thedescription, or may be learned by practice of the invention. The aspectsof the invention will be realized and attained by means of the elementsand combinations particularly pointed out in the appended claims. It isto be understood that both the foregoing general description and thefollowing detailed description are exemplary and explanatory only andare not restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute partof this specification, illustrate embodiments of the invention andtogether with the description, serve to explain the principles of theinvention. The embodiments illustrated herein are presently preferred,it being understood, however, that the invention is not limited to theprecise arrangements and instrumentalities shown, wherein:

FIG. 1 is a pictorial illustration of a supply chain adapted for privateinformation sharing utilizing a supply chain collaborative computingenvironment;

FIG. 2 is schematic illustration of the supply chain collaborativecomputing environment of FIG. 1;

FIG. 3 is a flow chart illustrating a process for managing events in thesupply chain collaborative computing environment of FIG. 2; and,

FIG. 4 is a diagram depicting a shared logistical environmentincorporating several different supply chain collaborative computingenvironments interoperating with one another to provide for privatesupply chain information sharing across different supply chains.

DETAILED DESCRIPTION OF THE INVENTION

Embodiments of the invention provide for an ad hoc supply chaincollaborative computing node adapted for supply chain informationsharing amongst actors in a supply chain so as to promote on demandsupply chain information sharing amongst participants in a supply chainin a private and secure manner. In accordance with an embodiment of theinvention, a participant in a supply chain configures a supply chaincollaborative computing environment as a collaborative computingenvironment. The configuration process begins with the selection from aset of collaboration models, a particular collaboration model consistentwith a type of the supply chain. The configuration proceeds with theinitialization, in accordance with the particular collaboration model,of a knowledge graph of a multiplicity of entities representative of theprospective actors and resources in the supply chain connected by edgesdefining relationships therebetween.

The configuration further continues with the definition of a set ofevents expected to occur in the supply chain in accordance with thecollaboration model. The configuration yet further continues with theregistration of different publisher and subscriber ones of the actors toan event log and providing authentication credentials to each of thepublisher and subscriber ones of the actors. Finally, the configurationcompletes with the specification, in accordance with the collaborationmodel, of one or more computational functions each computing apredictive supply chain value of the supply chain based upon eventswritten onto the event log by publisher ones of the actors. In this waya supply chain collaborative computing environment may be provisioned byan actor in the supply chain in a templated way according to a specifiedcollaboration model for the supply chain so as to permit the sharing ofinformation of the supply chain amongst participants in the supply chainin a private and confidential manner so as to promote supply chainresource utilization optimization.

In further illustration, FIG. 1 pictorially illustrates a supply chainadapted for private information sharing utilizing a supply chaincollaborative computing environment. As shown in FIG. 1, one or moreindividual actors 110 in a supply chain, ranging from a manufacturingsource 110A, to a transportation and logistics provider 110B, to a portof entry 110C to a distribution center 110D, select a collaborativemodel from amongst a selection of collaborative models 120. Thosecollaboration models 120 may include a particular type, for instance byway of example, at least one model directed to data sharing requirementsfor a retail stock optimization, at least one model directed to datasharing requirements for transportation and logistics resource andcapacity optimization, at least one model directed to data sharingrequirements for logistics pooling and integration for urbandistribution, at least one model directed to data sharing requirementsfor electronic compliance with governmental regulations, and at leastone model directed to data sharing requirements for supply chainfinancial management.

Each of the collaboration models 120 defines a specific type ofknowledge graph that includes different entities representative ofcorresponding actors and resources of the supply chain necessary tofulfill data sharing requirements of the different set, joined by edgesrepresentative of relationships between respectively joined ones of theentities. Each of the collaboration models 120 also defines a set ofevents expected to be received in connection with the data sharingrequirements such that different ones of the actors 110 may adaptinternal events to a format set forth for corresponding events of aselected one of the collaboration models 120. Finally, each of thecollaboration models 120 defines one or more predictive functionsoperating upon the set of events to produce predictive values, andoptionally, one or more KPIs 180 specific to a type of a selected one ofthe collaboration models 120.

Consequently, once one of the actors 110 selects a particular one of thecollaboration models 120, an ad hoc supply chain collaborative computingenvironment 100 is established in which supply chain data is sharedprivately and securely amongst the actors 110. As part of theestablishment of the ad hoc supply chain collaborative computingenvironment 100, supply chain collaborative computing environment logic130 creates a knowledge graph 150 of different entities representativeof the actors and resources of the supply chain, and edges connectingthe entities to one another representative of the relationships betweenthe entities, in accordance with the selected one of the collaborationmodels 120.

Supply chain collaborative computing environment logic 130 in the ad hocsupply chain collaborative computing environment 100 then registers eachof the actors 110 as a publisher of events to an event log 140. As well,the supply chain collaborative computing environment logic 130 registersselected ones of the actors 110 as subscribers to updated states for theentities of the knowledge graph 150. Finally, the supply chaincollaborative computing environment logic 130 maps events occurring ininformation systems of respective ones of the actors 110 to the eventsof the selected one of the collaboration models 120.

Once the ad hoc supply chain collaborative computing environment 100 hasbeen established, the supply chain collaborative computing environmentlogic 130 continuously monitors the event log 140 in order to processnew events published to the event log 140 by the registered ones of theactors 110 in accordance with events defined by the selected one of thecollaboration models 120. As the supply chain collaborative computingenvironment logic 130 detects a new event published to the event log140, the supply chain collaborative computing environment logic 130identifies one or more entities in the knowledge graph 150 implicated bythe new event. In turn, the supply chain collaborative computingenvironment logic 130 applies one or more predictive functions 160defined by the selected one of the collaboration models 120 to one ormore values specified by the new event and in connection with theimplicated entities so as to produce one or more updated values inconnection with the implicated entities and to post one or moreadditional events to the event log 140 encapsulating the updated values.As well, one or more of the KPIs 180 defined for the selected one of thecollaboration models 120 may be compared to the updated values in orderto produce a measurement of a difference therebetween. Consequently,subscribing ones of the actors 110 may query the event log 140 throughinterface 170 so as to enjoy real-time access to shared supply chaindata affected by the events published to the event log 140.

In more specific illustration of the ad hoc supply chain collaborativecomputing environment 100, FIG. 2 is schematic illustration of anexemplary ad hoc supply chain collaborative computing environment 200.An ad hoc supply chain collaborative computing environment may beimplemented in a host computing system 230 that includes one or morecomputers, each with memory and at least one processor. The hostcomputing system 230 may be communicatively coupled over computercommunications network to different information systems 220 fordifferent actors in a supply chain so that information may betransmitted to the host computing system 230 by the differentinformation systems 220, and information may be transmitted to thedifferent information systems 220 by the host computing system 230.

A virtual machine 240 may execute in the memory of the host computingsystem 230 and support the operation therein of an operating system250A. A data store 280 adapted to persist data is coupled to the hostcomputing system 230 and stores therein a knowledge graph 290 definingboth a multiplicity of entities, each entity corresponding to one of thedifferent actors or resources of the supply chain, and also therelationships between the entities, all in accordance with acollaboration model selected from amongst a list of collaboration modelsin a user interface of the host computing system 230. Optionally, thedata store 280 persists one or more contemporaneous values forcorresponding KPIs of the supply chain defined by the selectedcollaboration model. Finally, an event log 270 is established in thememory of the host computing system 230 in which different events areposted as defined by the selected collaboration model.

The operating system 250A may support the presence of one or moreapplication containers 250B. One of the application containers 250Bhosts the execution of a supply chain collaborative computingenvironment module 300. The supply chain collaborative computingenvironment module 300 includes program instructions that when executein the memory of the host computing system by way of the one of theapplication containers 250B, monitors the event log 270 to detect newevents published to the event log 270 by different ones of theinformation systems 220. The program instructions further process eachdetected event by applying one or more predictive functions defined bythe selected collaboration model, to data within the event and data ofone or more implicated entities in the knowledge graph 290 so as toproduce an updated state for one or more of the entities in theknowledge graph 290 and to publish an additional event to the event log270 reflective of the updated state. Optionally, the programinstructions compute for a given event a new value for one of the KPIsstored in the data store 280.

Notably, a query interface 260 is provided in the supply chaincollaborative computing environment 200. The query interface 260 may bea form driven user interface or an API providing programmatic access tothe knowledge graph 290. More particularly, the query interface 260provides a user interface accessible over the computer communicationsnetwork 210 into which different actors in the supply chain may beauthenticated into the supply chain collaborative computing environment,through which queries against the knowledge graph 290 and also the eventlog 270 may be received and through which result sets from the queriesmay be presented. In this way, the different actors of the supply chainmay access supply chain state information in a transparent and secureway.

In even yet further illustration of the operation of the supply chaincollaborative computing environment module 300, FIG. 3 is a flow chartillustrating a process for managing events in the supply chaincollaborative computing environment of FIG. 2. Beginning in block 310, anew event for the supply chain is received in the event log as havingbeen published by a registered publishing actor of the supply chain. Inblock 320, an entity in the knowledge graph for the supply chain may beidentified as having been implicated by the event. For instance, dataencapsulated in the event may be parsed to identify one or more entitiesalso present in the knowledge graph Likewise, in block 330, supply chaindata associated with the event may be extracted from the event.

In block 340, a predictor is determined as being relevant to theidentified entity or entities and the extracted data. Thereafter, inblock 350 a new state for the identified entity or entities may becomputed by applying the predictor as a function of pertinent data ofthe identified entity or entities and the extracted data. As such, inblock 360 a state of the entity or entities is updated to the new stateand the new state is then encapsulated into an additional even andposted onto the event log. Optionally, a new value for each of one ormore KPIs may be computed and stored in the supply chain collaborativecomputing environment. Finally, the process repeats in block 310 withthe receipt of a new event in the event log.

Of import, while it will be apparent that a single ad hoc supply chaincollaborative computing environment supports the transparent and securesharing of supply chain information amongst the participants in aspecific supply chain, the supply chain of FIG. 2 may be adapted toregister other supply chain collaborative computing environments as bothpublishers of events to the event log, and also as subscribers to stateinformation of the knowledge graph of FIG. 2. Indeed, different supplychain collaborative computing environments may bi-directionally registerone another so as to effectively integrate the contemporaneousprocessing of events occurring in two different corresponding supplychains. The foregoing is simply illustrated in FIG. 4 in which a sharedlogistical environment is shown incorporating several different supplychain collaborative computing environments 410A, 410B interoperatingwith one another to provide for private supply chain information torespectively different supply chain actors 400A, 400B sharing acrossdifferent supply chains.

The present invention may be embodied within a system, a method, acomputer program product or any combination thereof. The computerprogram product may include a computer readable storage medium or mediahaving computer readable program instructions thereon for causing aprocessor to carry out aspects of the present invention. The computerreadable storage medium can be a tangible device that can retain andstore instructions for use by an instruction execution device. Thecomputer readable storage medium may be, for example, but is not limitedto, an electronic storage device, a magnetic storage device, an opticalstorage device, an electromagnetic storage device, a semiconductorstorage device, or any suitable combination of the foregoing.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network. The computer readable program instructions mayexecute entirely on the user's computer, partly on the user's computer,as a stand-alone software package, partly on the user's computer andpartly on a remote computer or entirely on the remote computer orserver. Aspects of the present invention are described herein withreference to flowchart illustrations and/or block diagrams of methods,apparatus (systems), and computer program products according toembodiments of the invention. It will be understood that each block ofthe flowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein includes anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which includes one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

Finally, the terminology used herein is for the purpose of describingparticular embodiments only and is not intended to be limiting of theinvention. As used herein, the singular forms “a”, “an” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise. It will be further understood that the terms“includes” and/or “including,” when used in this specification, specifythe presence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

Having thus described the invention of the present application in detailand by reference to embodiments thereof, it will be apparent thatmodifications and variations are possible without departing from thescope of the invention defined in the appended claims as follows:

We claim:
 1. An ad hoc supply chain collaborative computing environmentfor use in a supply chain and adapted for private information sharing,the node comprising: a host computing system comprising one or morecomputers, each with memory and at least one processor; a data storecoupled to the host computing system and adapted to persist datatherein; a collaboration model loaded in the memory and selected fromamongst a multiplicity of collaboration models, each of thecollaboration models corresponding to a different set of data processingrequirements in a supply chain and acting as a template for an instanceof an ad hoc supply chain collaborative computing environment, each ofthe collaboration models defining: a specific type of knowledge graphcomprising different entities representative of corresponding actors andresources of the supply chain necessary to fulfill data processingrequirements of the different set, joined by edges representative ofrelationships between respectively joined ones of the entities, a set ofevents expected to be received in connection with the data sharingrequirements, and one or more predictive functions operating upon theset of events to produce predictive values; a knowledge graphinitialized in accordance with the selected collaboration model andpersisted in the data store and; an event log persisted in the datastore, the event log comprising different events published to the eventlog in accordance with the selected collaboration model by differentauthenticated computing systems of the actors; and, a supply chaincollaborative computing environment module comprising programinstructions executing in the memory of the host computing system inorder to perform: registering different ones of the actors asauthenticated publishers or subscribers to the event log and mappingevents occurring in information systems of respective ones of the actorsto the events of the selected collaboration model, authenticatingdifferent ones of the registered different ones of the actors prior thedifferent ones of the actors publishing events to the event log,triggering selected ones of the predictive functions for newly publishedones of the events mapped to the selected ones of the predictivefunctions in order to produce the predictive values, updating differentstates of the entities of the knowledge graph responsive to thepredictive values produced by the predictive functions, and providingread-only access to the different states of the entities of theknowledge graph to authenticated subscriber ones of the actors throughan interface to the supply chain collaborative computing environmentmodule.
 2. The ad hoc supply chain collaborative computing environmentof claim 1, wherein the program instructions are further enabled totransmit the different states of the entities of the knowledge graph toother supply chain collaborative computing environments in anaggregation of interoperable supply chain collaborative computingenvironments.
 3. The ad hoc supply chain collaborative computingenvironment of claim 1, wherein the node further comprises a searchengine interface configured to conduct search queries presented throughthe search engine interface against the knowledge graph.
 4. The ad hocsupply chain collaborative computing environment of claim 1, furthercomprising a set of key performance indicators (KPIs) defined in thedata store, wherein at least one of the predictive functions determinesa change in one of the KPIs based at least one of the newly publishedones of the events.
 5. The ad hoc supply chain collaborative computingenvironment of claim 1, further comprising one or more access rulesdisposed in the data store each rule defining a limitation on accessingstate information for the knowledge graph based upon an identity of acorresponding one of the actors seeking access to the knowledge graph.6. The ad hoc collaborative computing environment of claim 1, whereinthe collaboration models include at least one model directed to datasharing requirements for a retail stock optimization, at least one modeldirected to data sharing requirements for transportation and logisticsresource and capacity optimization, at least one model directed to datasharing requirements for logistics pooling and integration for urbandistribution, at least one model directed to data sharing requirementsfor electronic compliance with governmental regulations, and at leastone model directed to data sharing requirements for supply chainfinancial management.
 7. An ad hoc supply chain collaborative computingmethod, the method comprising: presenting in a user interface of a hostcomputing system, a list of collaboration models, each corresponding toa different set of data sharing requirements in a supply chain andacting as a template for an instance of an ad hoc supply chaincollaborative computing environment, each of the collaboration modelsdefining: a specific type of knowledge graph comprising differententities representative of corresponding actors and resources of thesupply chain necessary to fulfill data processing requirements of thedifferent set, joined by edges representative of relationships betweenrespectively joined ones of the entities, a set of events expected to bereceived in connection with the data sharing requirements, and one ormore predictive functions operating upon the set of events to producepredictive values selecting in the user interface, one of thecollaborative models and in response to the selection, initializing inthe memory of the host computing system in accordance with the selectedcollaboration model, a knowledge graph comprising different entitiesrepresentative of corresponding resources of the supply chain, joined byedges representative of relationships between respectively joined onesof the entities; registering by a processor of a host computing systemdifferent actors in a supply chain as authenticated publishers orsubscribers to an event log persisted in a data store coupled to thehost computing system and comprising different events defined inaccordance with the selected collaboration model and published to theevent log by different authenticated computing systems of the actors andmapping events occurring in information systems of respective ones ofthe actors to the events of the selected collaboration model;authenticating by the processor different ones of the registereddifferent actors prior the different actors publishing events to theevent log; triggering by the processor selected ones of the predictivefunctions for newly published ones of the events mapped to the selectedones of the predictive functions in order to produce the predictivevalues; modifying by the processor different states of the entities ofthe knowledge graph responsive to the predictive values produced by thepredictive functions; and providing by the processor read-only access tothe different states of the entities of the knowledge graph toauthenticated subscriber ones of the actors through an interface to thesupply chain collaborative computing environment module.
 8. The methodof claim 7, further comprising transmitting by the processor thedifferent states of the entities of the knowledge graph to other supplychain collaborative computing environments in an aggregation ofinteroperable supply chain collaborative computing environments.
 9. Themethod of claim 7, further comprising: receiving by the processor in asearch engine interface of the host computing system, a search query;and, conducting by the processor the search query against the knowledgegraph.
 10. The method of claim 8, further comprising defining by theprocessor a set of key performance indicators (KPIs) in the data store,wherein at least one of the predictive functions determines a change inone of the KPIs based at least one of the newly published ones of theevents.
 11. The method of claim 7, further comprising persisting by theprocessor one or more access rules in the data store each rule defininga limitation on accessing state information for the knowledge graphbased upon an identity of a corresponding one of the actors seekingaccess to the knowledge graph.
 12. The method of claim 7, wherein thecollaboration models include at least one model directed to data sharingrequirements for a retail stock optimization, at least one modeldirected to data sharing requirements for transportation and logisticsresource and capacity optimization, at least one model directed to datasharing requirements for logistics pooling and integration for urbandistribution, at least one model directed to data sharing requirementsfor electronic compliance with governmental regulations, and at leastone model directed to data sharing requirements for supply chainfinancial management.
 13. A computer program product for ad hoc supplychain collaborative computing the computer program product including acomputer readable storage medium having program instructions embodiedtherewith, the program instructions executable by a device to cause thedevice to perform a method including: presenting in a user interface ofa host computing system, a list of collaboration models, eachcorresponding to a different set of data processing requirements in asupply chain and acting as a template for an instance of an ad hocsupply chain collaborative computing environment, each of thecollaboration models defining: a specific type of knowledge graphcomprising different entities representative of corresponding actors andresources of the supply chain necessary to fulfill data sharingrequirements of the different set, joined by edges representative ofrelationships between respectively joined ones of the entities, a set ofevents expected to be received in connection with the data sharingrequirements, and one or more predictive functions operating upon theset of events to produce predictive values selecting in the userinterface, one of the collaborative models and in response to theselection, initializing in memory of the host computing system inaccordance with the selected collaboration model, a knowledge graphcomprising different entities representative of corresponding resourcesof the supply chain, joined by edges representative of relationshipsbetween respectively joined ones of the entities; registering by aprocessor of a host computing system different actors in a supply chainas authenticated publishers or subscribers to an event log persisted ina data store coupled to the host computing system and comprisingdifferent events defined in accordance with the selected collaborationmodel and published to the event log by different authenticatedcomputing systems of the actors and mapping events occurring ininformation systems of respective ones of the actors to the events ofthe selected collaboration model; authenticating by the processordifferent ones of the registered different actors prior the differentactors publishing events to the event log; triggering by the processorselected ones of the predictive functions for newly published ones ofthe events mapped to the selected ones of the predictive functions inorder to produce the predictive values; modifying by the processordifferent states of the entities of the knowledge graph responsive tothe predictive values produced by the predictive functions; andproviding by the processor read-only access to the different states ofthe entities of the knowledge graph to authenticated subscriber ones ofthe actors through an interface to the supply chain collaborativecomputing environment module.
 14. The computer program product of claim13, further comprising transmitting the different states of the entitiesof the knowledge graph to other supply chain collaborative computingenvironments in an aggregation of interoperable supply chaincollaborative computing environments.
 15. The computer program productof claim 13, further comprising: receiving in a search engine interfaceof the computer, a search query; and, conducting the search queryagainst the knowledge graph.
 16. The computer program product of claim14, further comprising defining a set of key performance indicators(KPIs) in the data store, wherein at least one of the predictivefunctions determines a change in one of the KPIs based at least one ofthe newly published ones of the events.
 17. The computer program productof claim 13, further comprising persisting one or more access rules inthe data store each rule defining a limitation on accessing stateinformation for the knowledge graph based upon an identity of acorresponding one of the actors seeking access to the knowledge graph.18. The computer program product of claim 13, wherein the collaborationmodels include at least one model directed to data sharing requirementsfor a retail stock optimization, at least one model directed to datasharing requirements for transportation and logistics resource andcapacity optimization, at least one model directed to data sharingrequirements for logistics pooling and integration for urbandistribution, at least one model directed to data sharing requirementsfor electronic compliance with governmental regulations, and at leastone model directed to data sharing requirements for supply chainfinancial management.